ServiceNow AI Research

Agents

Representing Positional Information in Generative World Models for Object Manipulation
Representing Positional Information in Generative World Models for Object Manipulation
The ability to predict outcomes of interactions between embodied agents and objects is paramount in the robotic setting. While …
Stefano Ferraro, Pietro Mazzaglia, Tim Verbelen, Sai Rajeswar Mudumba
Learning Effective Abstractions for Planning,  2024.
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An Ecosystem for Web Agents: WorkArena, BrowserGym, AgentLab and more
An Ecosystem for Web Agents: WorkArena, BrowserGym, AgentLab and more
The BrowserGym ecosystem addresses the growing need for efficient evaluation and benchmarking of web agents, particularly those …
Alexandre Lacoste, Maxime Gasse, Thibault Le Sellier De Chezelles, Massimo Caccia, Léo Boisvert, Megh Thakkar, Alexandre Drouin, Nicolas Chapados
Montreal AI Symposium (MAIS),  2024.
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Multimodal foundation world models for generalist embodied agents
Multimodal foundation world models for generalist embodied agents
Learning generalist embodied agents, able to solve multitudes of tasks in different domains is a long-standing problem. Reinforcement …
Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Aaron Courville, Sai Rajeswar Mudumba
Workshop at the International Conference of Machine Learning (ICML),  2024.
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WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
We study the use of large language model-based agents for interacting with software via web browsers. Unlike prior work, we focus on …
Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, Léo Boisvert, Megh Thakkar, Quentin Cappart, David Vazquez, Nicolas Chapados, Alexandre Lacoste
International Conference on Machine Learning (ICML),  2024.
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Evaluating In-Context Learning of Libraries for Code Generation
Evaluating In-Context Learning of Libraries for Code Generation
Contemporary Large Language Models (LLMs) exhibit a high degree of code generation and comprehension capability. A particularly …
Arkil Patel, Siva Reddy, Dzmitry Bahdanau, Pradeep Dasigi
North American Chapter of the Association for Computational Linguistics (NAACL),  2024.
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Efficient Dynamics Modeling in Interactive Environments with Koopman Theory
Efficient Dynamics Modeling in Interactive Environments with Koopman Theory
The accurate modeling of dynamics in interactive environments is critical for successful long-range prediction. Such a capability could …
Arnab Mondal, Siba Smarak Panigrahi, Siamak Ravanbakhsh, Sai Rajeswar Mudumba
International Conference of Learning Representations (ICLR),  2024.
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IntentGPT: Few-shot Intent Discovery with Large Language Models
IntentGPT: Few-shot Intent Discovery with Large Language Models
In today’s digitally driven world, dialogue systems play a pivotal role in enhancing user interactions, from customer service to …
Juan A. Rodriguez, Nicholas Botzer, David Vazquez, Christopher Pal, Marco Pedersoli, Issam H. Laradji
Workshop at the International Conference of Learning Representation (ICLR),  2024.
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WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks?
We study the use of large language model-based agents for interacting with software via web browsers. Unlike prior work, we focus on …
Alexandre Drouin, Maxime Gasse, Massimo Caccia, Issam H. Laradji, Manuel Del Verme, Tom Marty, David Vazquez, Nicolas Chapados, Alexandre Lacoste
Workshop at the International Conference of Learning Representation (ICLR),  2024.
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Workflow discovery in low data regimes
Workflow discovery in low data regimes
Text-based dialogues are now widely used to solve real-world problems. In cases where solution strategies are already known, they can …
Amine El Hattami, Issam H. Laradji, Stefania Raimondo, David Vazquez, Pau Rodriguez, Christopher Pal
International Conference of Learning Representations (ICLR),  2024.
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3rd Continual Learning Workshop Challenge on Egocentric Category and Instance Level Object Understanding
3rd Continual Learning Workshop Challenge on Egocentric Category and Instance Level Object Understanding
Continual Learning, also known as Lifelong or Incremental Learning, has recently gained renewed interest among the Artificial …
Lorenzo Pellegrini, Chenchen Zhu, Fanyi Xiao, Zhicheng Yan, Antonio Carta, Matthias De Lange, Vincenzo Lomonaco, Roshan Sumbaly, Pau Rodriguez, David Vazquez
ArXiv,  2024.
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